package other;


/**
 * Created by zhifengxie on 2017/3/28.
 */
public class LevenshteinSimilarityAlgorithm implements SimilarityAlgorithm
{
    @Override
    public double compute(String text, String compute)
    {
        return getSimilarityRatio(text,compute);
    }


    private int compare(String str, String target) {
        int d[][]; // 矩阵
        int n = str.length();
        int m = target.length();
        int i; // 遍历str的
        int j; // 遍历target的
        char ch1; // str的
        char ch2; // target的
        int temp; // 记录相同字符,在某个矩阵位置值的增量,不是0就是1

        if (n == 0) {
            return m;
        }

        if (m == 0) {
            return n;
        }

        d = new int[n + 1][m + 1]; //n行 m列

        for (i = 0; i <= n; i++) { // 初始化第一列
            d[i][0] = i;
        }

        for (j = 0; j <= m; j++) { // 初始化第一行
            d[0][j] = j;
        }

        for (i = 1; i <= n; i++) { // 遍历str
            ch1 = str.charAt(i - 1);
            // 去匹配target
            for (j = 1; j <= m; j++) {
                ch2 = target.charAt(j - 1);
                if (ch1 == ch2) {
                    temp = 0;
                } else {
                    temp = 1;
                }

                // 左边+1,上边+1, 左上角+temp取最小
                int one=d[i - 1][j] + 1;
                int two=d[i][j - 1] + 1;
                int three=d[i - 1][j - 1] + temp;
                d[i][j] =
                        min(one, two,
                                three);
            }
        }

        return d[n][m];
    }

    private int min(int one, int two, int three) {
        return
                (one = one < two ? one : two) < three ? one : three;//三个比较  返回最大的
    }

    /**
     * 获取两字符串的相似度
     *
     * @param str
     * @param target
     *
     * @return
     */

    public double getSimilarityRatio(String str, String target) {
        return 1 - (double) compare(str, target) / Math.max(str.length(), target.length());

    }

    public static void main(String[] args) {
        SimilarityAlgorithm similarityAlgorithm=new LevenshteinSimilarityAlgorithm();
        System.out.println(similarityAlgorithm.compute("米小","小米"));
    }

}
